Background and Problem

This template has been produced using the posterdown package. It generates a standard conference-style poster layout.

A common problem in clinical research is messed up data¹. It can lead to bias or nonsensical results. Appropriate statistical analysis can result in superb findings in such cases, with the right assumptions.

Data Sources and Datasets

The syntax in this poster template and the posterdown package uses the same workflow approach as the R Markdown you know and love.

You can even use the bibliography the same way: Our data were taken from a cluster-randomised trial ², available from the Irish Social Science Data Archive.

Early Results / Descriptive Statistics of Datasets

Usually you want to have a nice table displaying some important results that you have calculated. In posterdown this is as easy as using the kable table formatting you are probably use to as per typical R Markdown formatting.

You can reference tables like so: Table 1. Some basic summaries of the dataset are below:

Table 1: Table caption.

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width
5.1	3.5	1.4	0.2
4.9	3.0	1.4	0.2
4.7	3.2	1.3	0.2
4.6	3.1	1.5	0.2
5.0	3.6	1.4	0.2
5.4	3.9	1.7	0.4
4.6	3.4	1.4	0.3
5.0	3.4	1.5	0.2
4.4	2.9	1.4	0.2
4.9	3.1	1.5	0.1

Figure 1, and Figure 2 below show the patterns in our dataset. Make sure that all the details in your plots will be legible when printed (legend text, axis text, and any labels)

You can even make your plots interactive for the HTML version of the poster. You can use the HTML poster for the presentation session, and the PDF poster will be printed - so be sure the static version looks okay.

Next Project Steps

We plan to conduct further analysis using:

• Variable discombobulation ³
• Expand our minds with explosive machine learning ⁴.

We will use the plasticanalysis package for this.

GitHub

The code and datasets for this project can be viewed at our GitHub repository here: https://github.com/

References